Modelling activation of congestion control for estimating channel load in vehicular networks

In this paper, we present a Markov chain based model that can be used for easy estimation of the Vehicle to Vehicle (V2V) message generation rates in a highway environment based on just the traffic flow rate and the average vehicle speed on the highway. This allows for a faster estimation of the overall channel load than using a simulation environment to do the same. Our model considers the effects of Decentralized Congestion Control based on Transmit Rate Control (DCC-TRC) on Cooperative Awareness Message (CAM) generations. The model is evaluated by comparing the results obtained with the message generation rates achieved for a highway traffic scenario in a simulation environment based on Artery and SUMO. Comparing the results shows that the Cumulative Distributive Function (CDF) of the message generation rates estimated by our model is fairly accurate as they fall within the 95% confidence interval of the CDF obtained from the simulation.